Automatically selecting appropriate platform to run application in cloud computing environment

ABSTRACT

A method, system and computer program product for selecting an appropriate platform to run an application deployed in a cloud computing environment. The appropriate platform is selected by employing a two phase process, where the first phase occurs prior to the deployment of the application and the second phase occurs after the application has been deployed. In the first phase, the cloud computing node selects a platform using various factors, such as application binaries, application metadata and artifacts, and qualities of service and application requirements. In the second phase, the cloud computing node determines whether an alternative platform needs to be implemented for subsequent deployments of the application using various factors, such as application runtime metrics and garbage collection metrics. In this manner, an appropriate platform is automatically selected thereby removing the requirement for the user to indicate the type of platform for the target environment.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation application of pending U.S.patent application Ser. No. 13/356,811, which was filed on Jan. 24,2012, which is assigned to the assignee of the present invention. Thepresent application claims priority benefits to U.S. patent applicationSer. No. 13/356,811.

TECHNICAL FIELD

The present invention relates to cloud computing, and more particularlyto automatically selecting an appropriate platform (e.g., 32-bitplatform, 64-bit platform) to run an application deployed in the cloudcomputing environment.

BACKGROUND

In a cloud computing environment, computing is delivered as a servicerather than a product, whereby shared resources, software andinformation are provided to computers and other devices as a meteredservice over a network, such as the Internet. In such an environment,computation, software, data access and storage services are provided tousers that do not require knowledge of the physical location andconfiguration of the system that delivers the services.

Currently, application developers are required to decide which platform(e.g., 32-bit platform, 64-bit platform) to run their software deployedto the cloud computing environment. Such a decision has implications onboth runtime performance as well as efficient use of memory. Forexample, in some circumstances, an application may run faster on a64-bit platform rather than on a 32-bit platform at a cost of a largermemory footprint (program using or referencing a greater amount ofmemory while running). Conversely, some applications run slower in a64-bit environment though they have access to a greater amount ofmemory. Most application developers are not performance and memoryexperts, and hence they will have a difficult time in selecting theappropriate platform to optimize runtime performance and memoryutilization.

BRIEF SUMMARY

In one embodiment of the present invention, a method for selecting anappropriate platform to run an application deployed in a cloud computingenvironment comprises receiving application binaries. The method furthercomprises receiving qualities of service and application requirements.In addition, the method comprises analyzing the received applicationbinaries. Additionally, the method comprises analyzing the receivedqualities of service and application requirements. Furthermore, themethod comprises selecting, by a processor, a first platform to run theapplication to be deployed in the cloud computing environment based onthe analyzing of the received application binaries and the analyzing ofthe received qualities of service and application requirements.

Other forms of the embodiment of the method described above are in asystem and in a computer program product.

The foregoing has outlined rather generally the features and technicaladvantages of one or more embodiments of the present invention in orderthat the detailed description of the present invention that follows maybe better understood. Additional features and advantages of the presentinvention will be described hereinafter which may form the subject ofthe claims of the present invention.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

A better understanding of the present invention can be obtained when thefollowing detailed description is considered in conjunction with thefollowing drawings, in which:

FIG. 1 illustrates a network system configured in accordance with anembodiment of the present invention;

FIG. 2 illustrates a cloud computing environment in accordance with anembodiment of the present invention.

FIG. 3 illustrates a schematic of an exemplary cloud computing node inaccordance with an embodiment of the present invention;

FIG. 4 is a flowchart of a method for determining the appropriateplatform to run the application prior to the deployment of theapplication onto the cloud computing environment in accordance with anembodiment of the present invention; and

FIG. 5 is a flowchart of a method for validating the decision of theplatform selected in the first phase after the application has beendeployed onto the cloud computing environment in accordance with anembodiment of the present invention.

DETAILED DESCRIPTION

The present invention comprises a method, system and computer programproduct for selecting an appropriate platform to run an applicationdeployed in a cloud computing environment. In one embodiment of thepresent invention, the appropriate platform (i.e., the ideal runtimeenvironment for the application to be deployed onto the cloud computingenvironment) is selected by employing a two phase process, where thefirst phase occurs prior to the deployment of the application onto thecloud computing environment and the second phase occurs after theapplication has been deployed onto the cloud computing environment. Inthe first phase, the cloud computing node selects the platform (e.g.,32-bit platform) that optimizes runtime performance and memoryutilization using various factors, such as application binaries,application metadata and artifacts, and qualities of service andapplication requirements. In the second phase, the cloud computing nodedetermines whether an alternative platform needs to be implemented forsubsequent deployments of the application to optimize runtimeperformance and memory utilization using various factors, such asapplication runtime metrics and garbage collection metrics. In thismanner, the cloud computing node automatically selects an appropriateplatform (e.g., 32-bit platform, 64-bit platform) to optimize runtimeperformance and memory utilization thereby removing the requirement forthe user to indicate the type of platform (e.g., memory address buswidth) for the target environment.

While the following discusses the present invention in connection withselecting either the 32-bit platform or the 64-bit platform, theprinciples of the present invention may be applied to selecting anymemory address bus width that optimizes runtime performance and memoryutilization. A person of ordinary skill in the art would be capable ofapplying the principles of the present invention to suchimplementations. Further, embodiments applying the principles of thepresent invention to such implementations would fall within the scope ofthe present invention.

In the following description, numerous specific details are set forth toprovide a thorough understanding of the present invention. However, itwill be apparent to those skilled in the art that the present inventionmay be practiced without such specific details. In other instances,well-known circuits have been shown in block diagram form in order notto obscure the present invention in unnecessary detail. For the mostpart, details considering timing considerations and the like have beenomitted inasmuch as such details are not necessary to obtain a completeunderstanding of the present invention and are within the skills ofpersons of ordinary skill in the relevant art.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,the embodiments of the present invention are capable of beingimplemented in conjunction with any type of clustered computingenvironment now known or later developed.

In any event, the following definitions have been derived from the “TheNIST Definition of Cloud Computing” by Peter Mell and Timothy Grance,dated September 2011, which is cited on an Information DisclosureStatement filed herewith, and a copy of which is provided to the U.S.Patent and Trademark Office.

Cloud computing is a model for enabling ubiquitous, convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, servers, storage, applications, and services)that can be rapidly provisioned and released with minimal managementeffort or service provider interaction. This cloud model is composed offive essential characteristics, three service models, and fourdeployment models.

Characteristics are as follows:

On-Demand Self-Service: A consumer can unilaterally provision computingcapabilities, such as server time and network storage, as needed,automatically without requiring human interaction with each service'sprovider.

Broad Network Access: Capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, tablets, laptopsand workstations).

Resource Pooling: The provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according toconsumer demand. There is a sense of location independence in that theconsumer generally has no control or knowledge over the exact locationof the provided resources but may be able to specify location at ahigher level of abstraction (e.g., country, state or data center).Examples of resources include storage, processing, memory and networkbandwidth.

Rapid Elasticity: Capabilities can be elastically provisioned andreleased, in some cases automatically, to scale rapidly outward andinward commensurate with demand. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured Service: Cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth and active user accounts). Resource usage can bemonitored, controlled and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): The capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices througheither a thin client interface, such as a web browser (e.g., web-basede-mail) or a program interface. The consumer does not manage or controlthe underlying cloud infrastructure including network, servers,operating systems, storage, or even individual application capabilities,with the possible exception of limited user-specific applicationconfiguration settings.

Platform as a Service (PaaS): The capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages, libraries, servicesand tools supported by the provider. The consumer does not manage orcontrol the underlying cloud infrastructure including networks, servers,operating systems or storage, but has control over the deployedapplications and possibly configuration settings for theapplication-hosting environment.

Infrastructure as a Service (IaaS): The capability provided to theconsumer is to provision processing, storage, networks and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage anddeployed applications; and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private Cloud: The cloud infrastructure is provisioned for exclusive useby a single organization comprising multiple consumers (e.g., businessunits). It may be owned, managed and operated by the organization, athird party or some combination of them, and it may exist on or offpremises.

Community Cloud: The cloud infrastructure is provisioned for exclusiveuse by a specific community of consumers from organizations that haveshared concerns (e.g., mission, security requirements, policy andcompliance considerations). It may be owned, managed and operated by oneor more of the organizations in the community, a third party, or somecombination of them, and it may exist on or off premises.

Public Cloud: The cloud infrastructure is provisioned for open use bythe general public. It may be owned, managed and operated by a business,academic or government organization, or some combination of them. Itexists on the premises of the cloud provider.

Hybrid Cloud: The cloud infrastructure is a composition of two or moredistinct cloud infrastructures (private, community or public) thatremain unique entities, but are bound together by standardized orproprietary technology that enables data and application portability(e.g., cloud bursting for load balancing between clouds).

Referring now to the Figures in detail, FIG. 1 illustrates a networksystem 100 configured in accordance with an embodiment of the presentinvention. Network system 100 includes a client device 101 connected toa cloud computing environment 102 via a network 103. Client device 101may be any type of computing device (e.g., portable computing unit,personal digital assistant (PDA), smartphone, laptop computer, mobilephone, navigation device, game console, desktop computer system,workstation, Internet appliance and the like) configured with thecapability of connecting to cloud computing environment 102 via network103.

Network 103 may be, for example, a local area network, a wide areanetwork, a wireless wide area network, a circuit-switched telephonenetwork, a Global System for Mobile Communications (GSM) network,Wireless Application Protocol (WAP) network, a WiFi network, an IEEE802.11 standards network, various combinations thereof, etc. Othernetworks, whose descriptions are omitted here for brevity, may also beused in conjunction with system 100 of FIG. 1 without departing from thescope of the present invention.

Cloud computing environment 102 is used to deliver computing as aservice to client device 101 implementing the model discussed above. Anembodiment of cloud computing environment 102 is discussed below inconnection with FIG. 2.

FIG. 2 illustrates cloud computing environment 102 in accordance with anembodiment of the present invention. As shown, cloud computingenvironment 102 includes one or more cloud computing nodes 201 withwhich local computing devices used by cloud consumers, such as, forexample, personal digital assistant (PDA) or cellular telephone 202,desktop computer 203, laptop computer 204, and/or automobile computersystem 205 may communicate. Nodes 201 may communicate with one another.They may be grouped (not shown) physically or virtually, in one or morenetworks, such as Private, Community, Public, or Hybrid clouds asdescribed hereinabove, or a combination thereof. This allows cloudcomputing environment 102 to offer infrastructure, platforms and/orsoftware as services for which a cloud consumer does not need tomaintain resources on a local computing device. A description of aschematic of an exemplary cloud computing node 201 is provided below inconnection with FIG. 3. It is understood that the types of computingdevices 202, 203, 204, 205 shown in FIG. 2, which may represent clientdevice 101 of FIG. 1, are intended to be illustrative and that cloudcomputing nodes 201 and cloud computing environment 102 can communicatewith any type of computerized device over any type of network and/ornetwork addressable connection (e.g., using a web browser). Program codelocated on one of nodes 201 may be stored on a computer recordablestorage medium in one of nodes 201 and downloaded to computing devices202, 203, 204, 205 over a network for use in these computing devices.For example, a server computer in computing nodes 201 may store programcode on a computer readable storage medium on the server computer. Theserver computer may download the program code to computing device 202,203, 204, 205 for use on the computing device.

Referring now to FIG. 3, FIG. 3 illustrates a schematic of an exemplarycloud computing node 201 (FIG. 2) in accordance with an embodiment ofthe present invention. Cloud computing node 201 is only one example of asuitable cloud computing node and is not intended to suggest anylimitation as to the scope of use or functionality of embodiments of thepresent invention described herein. Regardless, cloud computing node 201is capable of being implemented and/or performing any of thefunctionality set forth herein.

In cloud computing node 201, there is a computer system/server 301,which is operational with numerous other general purpose or specialpurpose computing system environments or configurations. Examples ofwell-known computing systems, environments, and/or configurations thatmay be suitable for use with computer system/server 301 include, but arenot limited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 301 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingperformed by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 301 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 3, computer system/server 301 in cloud computing node201 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 301 may include, but are notlimited to, one or more processors or processor unit 302, a systemmemory 303 and a bus 304 that couples various system componentsincluding system memory 303 to processor unit 302.

Processor unit 302 executes instructions for software that may be loadedinto system memory 303. Processor unit 302 may be a number ofprocessors, a multi-processor core or some other type of processor,depending on the particular implementation. A number, as used hereinwith reference to an item, means one or more items. Further, processorunit 302 may be implemented using a number of heterogeneous processorsystems in which a main processor is present with secondary processorson a single chip. As another illustrative example, processor unit 302may be a symmetric multi-processor system containing multiple processorsof the same type.

Bus 304 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system/server 301 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 301, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 303 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 305 and/or cachememory 306. Computer system/server 301 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 307 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 304 by one or more datamedia interfaces. As will be further depicted and described below,memory 303 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the present invention.

Program/utility 308, having a set (at least one) of program modules 309,may be stored in memory 303 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 309 generally carry out the functionsand/or methodologies of embodiments of the present invention asdescribed herein.

Computer system/server 301 may also communicate with one or moreexternal devices 310 such as a keyboard, a pointing device, a display311, etc.; one or more devices that enable a user to interact withcomputer system/server 301; and/or any devices (e.g., network card,modem, etc.) that enable computer system/server 301 to communicate withone or more other computing devices. Such communication can occur viaI/O interfaces 312. Still yet, computer system/server 301 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 313. As depicted, network adapter 313communicates with the other components of computer system/server 301 viabus 304. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 301. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, data archival storage systems, etc.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” ‘module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or flash memory), a portablecompact disc read-only memory (CD-ROM), an optical storage device, amagnetic storage device, or any suitable combination of the foregoing.In the context of this document, a computer readable storage medium maybe any tangible medium that can contain, or store a program for use byor in connection with an instruction execution system, apparatus, ordevice.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the C programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of thepresent invention. It will be understood that each block of theflowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer program instructions. These computer programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunction/acts specified in the flowchart and/or block diagram block orblocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the function/acts specified in the flowchart and/or blockdiagram block or blocks.

As stated in the Background section, application developers arecurrently required to decide which platform (e.g., 32-bit platform,64-bit platform) to run their software deployed to the cloud computingenvironment. Such a decision has implications on both runtimeperformance as well as efficient use of memory. For example, in somecircumstances, an application may run faster on a 64-bit platform ratherthan on a 32-bit platform at a cost of a larger memory footprint(program using or referencing a greater amount of memory while running)Conversely, some applications run slower in a 64-bit environment thoughthey have access to a greater amount of memory. Most applicationdevelopers are not performance and memory experts, and hence they willhave a difficult time in selecting the appropriate platform to optimizeruntime performance and memory utilization.

The principles of the present invention provide a means for a cloudcomputing node 201 (FIGS. 2 and 3) to automatically select anappropriate platform (e.g., 32-bit platform, 64-bit platform) tooptimize runtime performance and memory utilization thereby removing therequirement for the user to indicate the type of platform (e.g., memoryaddress bus width) of their target environment as discussed below inconnection with FIGS. 4-5. In one embodiment, the appropriate platform(i.e., the ideal runtime environment for the application to be deployedonto cloud computing environment 102 of FIGS. 1 and 2) is selected byemploying a two phase process, where the first phase (discussed inconnection with FIG. 4) occurs prior to the deployment of theapplication onto cloud computing environment 102 and the second phase(discussed in connection with FIG. 5) occurs after the application hasbeen deployed onto cloud computing environment 102. FIG. 4 is aflowchart of a method for determining the appropriate platform to runthe application prior to the deployment of the application onto cloudcomputing environment 102. FIG. 5 is a flowchart of a method forvalidating the decision of the platform selected in the first phaseafter the application has been deployed onto cloud computing environment102.

FIG. 4 is a flowchart of a method 400 for determining the appropriateplatform to run the application prior to the deployment of theapplication onto cloud computing environment 102 in accordance with anembodiment of the present invention.

Referring to FIG. 4, in conjunction with FIGS. 1-3, in step 401, cloudcomputing node 201 receives application binaries (e.g., Java® classfiles, binaries written in non-interpreted programming languages) fromthe user.

In step 402, cloud computing node 201 receives application metadata andartifacts. Metadata refers to data providing information about one ormore aspects of the data, such as the purpose of the data, time and dateof creation, standards used, etc. Artifacts refer to the tangibleby-products (e.g., use cases, class diagrams, UML models, designdocuments) produced during the development of software.

In step 403, cloud computing node 201 receives qualities of service andapplication requirements. For example, qualities of service andapplication requirements guarantee a certain level of performance. Forexample, a required bit rate, delay, jitter, packet dropping probabilityand/or bit error rate may be guaranteed.

In step 404, cloud computing node 201 analyzes the received applicationbinaries in connection with determining which platform is to be selectedto run the application to be deployed in cloud computing environment 102as discussed further below. For example, the analysis may involvedetermining whether the application significantly utilizes BigIntegeroperations that can be optimized in a 64-bit platform. In anotherexample, the analysis may involve determining whether the applicationutilizes 32-bit native libraries that may negate the consideration ofusing a 64-bit platform.

In step 405, cloud computing node 201 analyzes the received applicationmetadata and artifacts in connection with determining which platform isto be selected to run the application to be deployed in cloud computingenvironment 102 as discussed further below. For example, the analysismay involve detecting if the application serves as a cache for otherapplications. By serving as a cache for other applications, a largermemory size for the heap may be required thereby necessitating aplatform with a greater memory address bus width (e.g., 64-bit platformversus a 32-bit platform). In another example, the analysis may involvedetermining if the service leverages an internal cache of a targetapplication server. By leveraging an internal cache of a targetapplication server, a smaller memory address bus width may be required.

In step 406, cloud computing node 201 analyzes the received qualities ofservice and application requirements in connection with determiningwhich platform is to be selected to run the application to be deployedin cloud computing environment 102 as discussed further below. Forexample, the analysis may involve determining whether the user hasspecified an explicit minimum/maximum memory requirement. For instance,if the minimum and maximum memory requirements may be satisfied with a32-bit platform, then a 32-bit platform may be selected. However, if theminimum memory requirement requires a 64-bit platform, then a 64-bitplatform may be selected. In another example, the analysis may involvedetermining whether there is a quality of service that could not beguaranteed due to the garbage collection pauses associated with largeheaps. Garbage collection may have a nondeterministic impact onexecution time by potentially introducing pauses into the execution of aprogram which are not correlated with the algorithm being processed. Ifthe pauses cause the quality of service (e.g., latency) for a givenplatform (e.g., 32-bit platform) to not be guaranteed, then analternative platform (e.g., 64-bit platform) may be selected.

In step 407, cloud computing node 201 selects the platform (e.g., 32-bitplatform) to run the application to be deployed in cloud computingenvironment 102 based on the analysis discussed above in steps 404-406.In such analysis, an initial decision is made as to select a particularplatform (e.g., 32-bit platform, 64-bit platform) that optimizes runtimeperformance and memory utilization using the factors (e.g., applicationbinaries, application metadata and artifacts, and qualities of serviceand application requirements) discussed above.

In some implementations, method 400 may include other and/or additionalsteps that, for clarity, are not depicted. Further, in someimplementations, method 400 may be executed in a different orderpresented and that the order presented in the discussion of FIG. 4 isillustrative. Additionally, in some implementations, certain steps inmethod 400 may be executed in a substantially simultaneous manner or maybe omitted.

After the initial deployment of the application onto cloud computingenvironment 102, the application runtime metrics are used to validatethe platform selected by cloud computing node 201 in step 407 of method400. Such validation occurs in a second phase as discussed below inconnection with FIG. 5. If the application runtime metrics indicate thatthe current environment (i.e., the selected platform) provides optimumperformance, the selected platform will continue to be used forsubsequent deployments of this application. However, if the applicationruntime metrics indicate that another platform would enable betterperformance, then such a platform will be used for subsequentdeployments of the application.

FIG. 5 is a flowchart of a method 500 for validating the decision of theplatform selected in the first phase after the application has beendeployed onto cloud computing environment 102 in accordance with anembodiment of the present invention.

Referring to FIG. 5, in conjunction with FIGS. 1-3, in step 501, cloudcomputing node 201 receives an indication that the application has beendeployed onto cloud computing environment 102.

In step 502, cloud computing node 201 receives application runtimemetrics and garbage collection metrics to validate the platform selectedby cloud computing node 201 in step 407 of method 400. Applicationruntime metrics include native memory utilization logs which provideinformation regarding native memory utilization, where native memoryrefers to the memory managed by the operating system. Garbage collectionmetrics include garbage collection logs that provide informationregarding the process (e.g., rate of collection) in reclaiming garbageor memory occupied by objects that are no longer in use by the program.Garbage collection, as used herein, refers to any type of automaticmemory management. Garbage collection is not to be limited in scope tothe use of garbage collection in Java®.

In step 503, cloud computing node 201 analyzes the garbage collectionmetrics in connection with validating the platform selected by cloudcomputing node 201 in step 407 of method 400 as discussed further below.For example, the analysis may involve determining whether the rate ofgarbage collection is too fast or slow. If it is too slow, then aplatform with a greater memory address bus width may be desired.Conversely, if it is too fast, then a platform with a smaller memoryaddress bus width may be desired. In another example, the analysis mayinvolve determining whether the pause time during the garbage collectionis acceptable for the indicated qualities of service. If not, then analternative platform may be desired.

In step 504, cloud computing node 201 analyzes the native memoryutilization in connection with validating the platform selected by cloudcomputing node 201 in step 407 of method 400 as discussed further below.For example, the analysis may involve utilizing native memoryutilization logs which provide information regarding utilizationpatterns. For instance, if memory is not being utilized greatly, then aplatform with a smaller memory address bus width may be desired.

In step 505, cloud computing node 201 analyzes the quality of serviceresults by correlating the memory usage with the received applicationruntime metrics in connection with validating the platform selected bycloud computing node 201 in step 407 of method 400 as discussed furtherbelow. For example, the analysis may involve determining whether thequalities of service are being met in worst case situations wheregarbage collection pauses occur. If such qualities of services are notbeing met, then an alternative platform may be desired.

In step 506, a determination is made by cloud computing node 201 as towhether to select an alternative the platform to support subsequentdeployments of the application based on the analysis discussed above insteps 503-505. In such analysis, a decision is made as to whether analternative platform to the one initially selected in step 407 of method400 needs to be implemented for subsequent deployments of theapplication to optimize runtime performance and memory utilization usingthe factors (e.g., application runtime metrics, garbage collectionmetrics) discussed above.

If an alternative platform is to be used to optimize runtime performanceand memory utilization for subsequent deployments of the application,then, in step 507, cloud computing node 201 selects an alternativeplatform to be used for subsequent deployments of the application.

If, however, an alternative platform is not to be used to optimizeruntime performance and memory utilization for subsequent deployments ofthe application, then, in step 508, the initially selected platform iscontinued to be used for subsequent deployments of the application.

In this manner, the initial selection of the platform to run theapplication deployed on cloud computing environment 102 is validatedusing actual user load.

In some implementations, method 500 may include other and/or additionalsteps that, for clarity, are not depicted. Further, in someimplementations, method 500 may be executed in a different orderpresented and that the order presented in the discussion of FIG. 5 isillustrative. Additionally, in some implementations, certain steps inmethod 500 may be executed in a substantially simultaneous manner or maybe omitted.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

The invention claimed is:
 1. A method for selecting an appropriateplatform to run an application deployed in a cloud computingenvironment, the method comprising: receiving application binaries;receiving qualities of service and application requirements; analyzingsaid received application binaries; analyzing said received qualities ofservice and application requirements; and selecting, by a processor, afirst platform to run said application to be deployed in said cloudcomputing environment based on said analyzing of said receivedapplication binaries and said analyzing of said received qualities ofservice and application requirements; wherein application runtimemetrics are used to validate said first platform selected to run saidapplication, wherein a second platform is selected to run saidapplication in response to said application runtime metrics indicatingthat said second platform would enable better performance.
 2. The methodas recited in claim 1 further comprising: receiving application metadataand artifacts; and analyzing said received application metadata andartifacts.
 3. The method as recited in claim 2 further comprising:selecting said first platform to run said application to be deployed insaid cloud computing environment based on said analyzing of saidreceived application binaries, said analyzing of said received qualitiesof service and application requirements and said analyzing of saidreceived application metadata and artifacts.
 4. The method as recited inclaim 1 further comprising: receiving said application runtime metricsand garbage collection metrics to validate said selection of said firstplatform.
 5. The method as recited in claim 4 further comprising:analyzing said garbage collection metrics; analyzing native memoryutilization; and analyzing said qualities of service by correlatingmemory usage with said received application runtime metrics.
 6. Themethod as recited in claim 5 further comprising: selecting said secondplatform based on said analyzing of said garbage collection metrics,said analyzing of said native memory utilization and said analyzing ofsaid qualities of service by correlating said memory usage with saidreceived application runtime metrics.
 7. The method as recited in claim1, wherein said first platform is one of a 32-bit platform and a 64-bitplatform.